With the wide availability of wireless and satellite connections to online services, users are increasingly relying on location search services to find destinations. Services such as Windows Local Live Search™ often provide users with traditional maps of locations, aerial photographs of those same locations, and/or combinations of photographs and maps.
In addition, the services often annotate these maps and photographs with identifiers for landmarks, businesses, and/or other points of interest. These annotations are often drawn from large datasets of location entities. The location entities are in turn often classified as “point of interest” (POI) entities or “yellow page” (YP) entities. POI entities are often created by users with mobile, GPS-enabled devices. Accordingly, the GPS coordinates for such entities tend to have a high degree of accuracy. Other fields of POI entities (e.g., name, address, etc.), however, tend to be less accurate as the entity-creating user may not enter those fields with a great degree of care. YP entities are often created by the businesses or locations that they identify, and may be captured for the dataset by, for example, crawling the Internet. Because YP entities are often created by businesses or locations having a strong desire to be found, name and address fields of the entities may be highly accurate. GPS coordinates for YP entities are then geo-coded based on the address field and vary in quality based on the accuracy of the address field.
These large datasets often include a number of entities with erroneous location information, resulting in location identifiers being placed on maps at the wrong locations. While location entities with erroneous location information may be manually located and deleted, doing so can be time and labor intensive.